In this paper, we presentDIB-R, a differentiable rendering framework which allows gradients to be analytically computed for allpixels inanimage.

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Experiments demonstrate that our editing scheme based on 3D-SDN is superior to its 2D counterpart.

Which allows to conclude that the sigmoid corresponds to the Heaviside function perturbed with a logistic noise. As introduced in the paper, control variates methods can be used to reduce the noise of the Monte-Carlo estimators of the Jacobian of a perturbed renderer, without inducing any extra-computation. Proposition 5. Jacobian of perturbed renderers can be written as: J We adapt the previous proof to the case of a Cauchy distribution for the noise. Z 1 (67) remains valid. Z 1 (73) 17 Figure 9: Pose optimization with an initial guess uniformly sampled on the rotation space.